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Paper Citation Record · LEDGER

Scalable Strategies for Continual Learning with Replay

As of 19 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 2 inbound Pith citation observations for arXiv:2505.12512.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.12512 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:36:40.017952Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:52:45.940026Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-12T07:31:37.973339Z

Reference resolution

61 of 61 outbound references displayed

  • verified exact3
  • verified fuzzy23
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 985f05ce-91b7-4ef2-8f84-84997dd1a033 · outbound

This paper cites Ss-il: Separated softmax for incremental learning.

Scalable Strategies for Continual Learning with Replay Ss-il: Separated softmax for incremental learning

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.163084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.685795Z digest=sha256:f9e3a0a3ad990f1a4f67fd6a8272287f9ccb80446348219fd17c364d9e655064

Observation 7471c7ee-c21e-405e-b589-346dcdc6b39c · outbound

This paper cites Distillation Scaling Laws.

Scalable Strategies for Continual Learning with Replay Distillation Scaling Laws

Reference 2

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no resolver link, observed 2026-08-15T20:36:39.691481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.691481Z digest=sha256:b1b084a6adf858f45840d3b5b507b1f58891da70b83ee70107f1c3f93c2b9390

Observation 6e9377d6-5dd5-4767-b7da-1084cac78dad · outbound

This paper cites Dark experience for general continual learning: a strong, simple baseline.Advances in Neural Information Processing Systems, 33:15920–15930, 2020.

Scalable Strategies for Continual Learning with Replay Dark experience for general continual learning: a strong, simple baseline.Advances in Neural Information Processing Systems, 33:15920–15930, 2020

Reference 3

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no resolver link, observed 2026-08-15T20:36:39.696283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.696283Z digest=sha256:d207998ffcb6c4f4374004f2e435ccd01adba71d0b2aeb0ad3d861f544a7065d

Observation 788d1a61-bef7-4ca7-b183-ddda899cfdb8 · outbound

This paper cites A Survey on In-context Learning.

Scalable Strategies for Continual Learning with Replay A Survey on In-context Learning

Reference 4

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no resolver link, observed 2026-08-15T20:36:39.701007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.701007Z digest=sha256:5ccd828b8817a6aff411081b54e6df4599f0465fe48fb1b39c0058cdcb93806e

Observation bd8ccb5d-a93a-4858-9a25-4ef4e49d2a08 · outbound

This paper cites The Llama 3 Herd of Models.

Scalable Strategies for Continual Learning with Replay The Llama 3 Herd of Models

Reference 5

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unresolved
no resolver link, observed 2026-08-15T20:36:39.705276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.705276Z digest=sha256:a4b4198d3b391cf9815c9fdb00f0b5d3a14dac62aa8f590fb72dec5bb6e0ba3d

Observation e1f1c890-244a-4890-bbb2-2137017cc03d · outbound

This paper cites A unified continual learn- ing framework with general parameter-efficient tuning.

Scalable Strategies for Continual Learning with Replay A unified continual learn- ing framework with general parameter-efficient tuning

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.139931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.709463Z digest=sha256:41b62a4b23d34e360d8a86e39fc3e906241ca055d6db14dd28c17e6d690bdbeb

Observation 859c610a-853a-4703-abb8-f362e8785436 · outbound

This paper cites TiC-CLIP: Continual Training of CLIP Models.

Scalable Strategies for Continual Learning with Replay TiC-CLIP: Continual Training of CLIP Models

Reference 7

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no resolver link, observed 2026-08-15T20:36:39.713990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.713990Z digest=sha256:8b7bec7ab517dfb175e356412be7949d50e71dcf89ae48e49855461fe4e634f8

Observation 3d9e1a87-df4d-4b01-bc48-73f02e670776 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Scalable Strategies for Continual Learning with Replay DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

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no resolver link, observed 2026-08-15T20:36:39.719480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.719480Z digest=sha256:b357cb38e5eb067d06e268a1c1b966671b0324523b7e1d876c173db27378562d

Observation 6f80fae7-e518-4f9f-bf7d-33a0f627933e · outbound

This paper cites Rusu, and Razvan Pascanu.

Scalable Strategies for Continual Learning with Replay Rusu, and Razvan Pascanu

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.125192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.725893Z digest=sha256:7a5aa3b00c61d7de082910d0fb116c1a0deacd8c4167c53f0bbb08ea38deb327

Observation 3870a8a1-62b1-453f-b26d-1e10f0a3636b · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Scalable Strategies for Continual Learning with Replay Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 10

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no resolver link, observed 2026-08-15T20:36:39.730477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.730477Z digest=sha256:b8c43b5c09c6b4f1429b5a1520c1b9c1ede89a775bfe8af6e80615ed26e46818

Observation f922df78-30c3-4c7a-b258-5f3f7f8d154b · outbound

This paper cites Hayes, Ronald Kemker, and Christopher Kanan.

Scalable Strategies for Continual Learning with Replay Hayes, Ronald Kemker, and Christopher Kanan

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.111002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.736161Z digest=sha256:45c3c50565f881992a4ed9aeb61b1d09bb8efb347b91d9a68b61d6bf5116d06e

Observation 495ee9ba-6910-41ed-afb2-c690a904f61f · outbound

This paper cites Replay in Deep Learning: Current Approaches and Missing Biological Elements.

Scalable Strategies for Continual Learning with Replay Replay in Deep Learning: Current Approaches and Missing Biological Elements

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:36:40.627276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.741283Z digest=sha256:3bf82e395bef70ba7457ecd1186fdb13679e5e7a14fe969f4762342b904466e6

Observation 97881e55-a423-42f2-9ce6-24de3d6228ea · outbound

This paper cites Watch Your Step: Optimal Retrieval for Continual Learning at Scale.

Scalable Strategies for Continual Learning with Replay Watch Your Step: Optimal Retrieval for Continual Learning at Scale

Reference 13

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no resolver link, observed 2026-08-15T20:36:39.748015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.748015Z digest=sha256:a48091ea2975650d711d2b33bb3e112c9ce0ec7dbbc3b25a096573177dd3e197

Observation 33d4d77b-8cb5-4845-aa0f-ac8351a737b3 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Scalable Strategies for Continual Learning with Replay Distilling the Knowledge in a Neural Network

Reference 14

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no resolver link, observed 2026-08-15T20:36:39.757280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.757280Z digest=sha256:aa67b3aff8e973fe5efe1c9d7e0a0b6399ce76f0471e6a4a4fd43b236e92c202

Observation c24566ed-89be-4730-9c1f-824c4bf8f4ec · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Scalable Strategies for Continual Learning with Replay Parameter-efficient transfer learning for nlp

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.098287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.764504Z digest=sha256:92f098e9c538c107ab56fd552b3b631f4c92ff545e1fddb29312da73a8cc8677

Observation 3224e36d-6780-43dc-9465-543921014df8 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Scalable Strategies for Continual Learning with Replay Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.084908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.770037Z digest=sha256:868dcacccd8e5d1185d070738961f2c90db28958c96e2ca918b7f03de035264b

Observation 6a5429c5-cdd9-4625-8a41-beb6d3d51615 · outbound

This paper cites A Survey on Retrieval-Augmented Text Generation for Large Language Models.

Scalable Strategies for Continual Learning with Replay A Survey on Retrieval-Augmented Text Generation for Large Language Models

Reference 17

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no resolver link, observed 2026-08-15T20:36:39.774836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.774836Z digest=sha256:3955f544213fed0fc79985f466916cbcacb9fa46b45461e5cb6c0723be55a4cc

Observation 8888d7a0-a06f-4b9f-affa-669abc410381 · outbound

This paper cites Position: Open-endedness is essential for artificial superhuman intelligence.

Scalable Strategies for Continual Learning with Replay Position: Open-endedness is essential for artificial superhuman intelligence

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.070832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.779833Z digest=sha256:3e132a4ad8133b23f667e93f69f649cb6196be3dc12ec36f39df0770b081a83e

Observation 2c718bbd-17db-4aa6-b20e-c781404f3d96 · outbound

This paper cites Simple and Scalable Strategies to Continually Pre-train Large Language Models.

Scalable Strategies for Continual Learning with Replay Simple and Scalable Strategies to Continually Pre-train Large Language Models

Reference 19

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no resolver link, observed 2026-08-15T20:36:39.784001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.784001Z digest=sha256:7bc499e05bf27655761dd21eaa206763e8ff9e733d8898def8908bbe38fed47f

Observation 7e1a2f26-a80c-47e1-bb98-8354b09bd90d · outbound

This paper cites Open- clip, 2021.

Scalable Strategies for Continual Learning with Replay Open- clip, 2021

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.054406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.788881Z digest=sha256:1506f9c2d84ece7bdd5b0ff0d3c2aa52166f29d0d5df182b6084f008f414e812

Observation e6d95999-68ee-400b-8c66-2b9bc6e87e53 · outbound

This paper cites Editing Models with Task Arithmetic.

Scalable Strategies for Continual Learning with Replay Editing Models with Task Arithmetic

Reference 21

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unresolved
no resolver link, observed 2026-08-15T20:36:39.793386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.793386Z digest=sha256:5ec371324a3099964bb5bd1aa16de943355c24b46ac41159d84e8017f7f36ea7

Observation 61bac005-b78d-486d-9202-919e9cb24b05 · outbound

This paper cites Unlocking the power of function vectors for characterizing and mitigating catastrophic forgetting in continual instruction tuning.

Scalable Strategies for Continual Learning with Replay Unlocking the power of function vectors for characterizing and mitigating catastrophic forgetting in continual instruction tuning

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.040915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.798482Z digest=sha256:a4dfb965b3b81bc641ea6d092d733f5cb6c6110d1d2191c13611f57919009874

Observation 7f555cfc-9042-4487-a01a-3751b809df4a · outbound

This paper cites Continual pre-training of lan- guage models.

Scalable Strategies for Continual Learning with Replay Continual pre-training of lan- guage models

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.025125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.803852Z digest=sha256:d2df426588886f6e96a6400d2dad013e17c086ce745d5eb76655e1ea90429788

Observation f0dd6fb5-fd24-45e8-af91-82822e4cdef4 · outbound

This paper cites Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A.

Scalable Strategies for Continual Learning with Replay Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.010130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.808375Z digest=sha256:a5286d9b6a5f8910c58f24f68e94ddcf94f133ca182095479c05c2150264341a

Observation 13765f42-efc1-43d7-a60e-41d34c6af33d · outbound

This paper cites McClel- land.

Scalable Strategies for Continual Learning with Replay McClel- land

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.995704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.812304Z digest=sha256:d2a8a0770d99e81cced99791fa07bf3511cb26b2300fc4a9e04a6fcbcb512c58

Observation 1d6be6db-a26c-482c-bf29-50f6b9ca3087 · outbound

This paper cites The power of scale for parameter-efficient prompt tuning.

Scalable Strategies for Continual Learning with Replay The power of scale for parameter-efficient prompt tuning

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.980529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.817843Z digest=sha256:65a8de65317dcc41d9b82f77018d6f3fc0c651fdc8b171e6810c5ef20475540d

Observation 3d4106fb-e760-4675-9a09-5a98e81deb17 · outbound

This paper cites Eurekaverse: Environment Curriculum Generation via Large Language Models.

Scalable Strategies for Continual Learning with Replay Eurekaverse: Environment Curriculum Generation via Large Language Models

Reference 27

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no resolver link, observed 2026-08-15T20:36:39.822334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.822334Z digest=sha256:63472921ed774c5c68555c05207830b8630cbfe97a2ef7878b2005006ab95a1f

Observation 3827d59c-ad38-4f1a-9a14-cb402e741ab5 · outbound

This paper cites Loss decoupling for task- agnostic continual learning.

Scalable Strategies for Continual Learning with Replay Loss decoupling for task- agnostic continual learning

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.967764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.827875Z digest=sha256:cd5d6ebd958a39e09489c1b7864f84a56cf736054ca3aecf0f00b3ce3a94c215

Observation c1f271fa-c67b-46e2-bd0a-1e4a7ffcc0b4 · outbound

This paper cites A Survey of In-Context Reinforcement Learning.

Scalable Strategies for Continual Learning with Replay A Survey of In-Context Reinforcement Learning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.832090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.832090Z digest=sha256:04d4a53b8a602cf91617fda8f5f701c6c1ea62987c04c787bd78042179a8a741

Observation 455113d9-aa82-437a-a1f9-e2718abeca46 · outbound

This paper cites Task arithmetic in the tangent space: Improved editing of pre-trained models.

Scalable Strategies for Continual Learning with Replay Task arithmetic in the tangent space: Improved editing of pre-trained models

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.952431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.837751Z digest=sha256:1bd745ad23f4c0ab31dc342741300ef443b8bddaef34d8ca8cd8e7a612e4cfcc

Observation 28fd64b7-a0d6-4a7f-9e56-ffd91e4277df · outbound

This paper cites R+X: Retrieval and Execution from Everyday Human Videos.

Scalable Strategies for Continual Learning with Replay R+X: Retrieval and Execution from Everyday Human Videos

Reference 31

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unresolved
no resolver link, observed 2026-08-15T20:36:39.842118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.842118Z digest=sha256:0f8a266c83b72a8a20173190666ad8e76cf86a9439c867ea88361da308552624

Observation 98194bbd-0b94-46e3-9f1f-33ed707f5209 · outbound

This paper cites Berg, and Li Fei-Fei.

Scalable Strategies for Continual Learning with Replay Berg, and Li Fei-Fei

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.936323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.850282Z digest=sha256:ab1459f24fe42a6492e5bab47a6b42f52264366ee74e5c96c8aba087d19b6986

Observation 0c0baaa2-7591-4ba1-b17a-d09cb7dbf5ca · outbound

This paper cites Progressive Neural Networks.

Scalable Strategies for Continual Learning with Replay Progressive Neural Networks

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.855457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.855457Z digest=sha256:223f3a3c5a15b75ccd3ede3653ccb7a2f2add238a1e0db300f5b8f73c6f08573

Observation c7cd136f-cd94-4286-ac17-1aa84e3c8e58 · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 34

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unresolved
raw_fallback, observed 2026-08-15T20:36:40.921579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.860939Z digest=sha256:d83bc1e6fa8e1981baddf919173b23832b489959dc3d4185d73b576fff1b8fdb

Observation 15020da6-b3f2-429a-81ca-394ab6548143 · outbound

This paper cites A Closer Look at Rehearsal-Free Continual Learning.

Scalable Strategies for Continual Learning with Replay A Closer Look at Rehearsal-Free Continual Learning

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:36:40.402912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.865942Z digest=sha256:83e7c5bb76ec9f3d142d6f3ee7ddf8358f983e93602e7f62144244257db3f2d8

Observation e05a5980-71c8-4beb-a424-7a969622d53a · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Scalable Strategies for Continual Learning with Replay Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 36

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no resolver link, observed 2026-08-15T20:36:39.872490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.872490Z digest=sha256:09e25443e97f842cde8b8943411f0a317bf8d0855579b55ac820ce39c4db916d

Observation 4dd46f1b-11be-4283-b32a-6f773cc1f83d · outbound

This paper cites Improving online continual learning performance and stability with temporal ensembles.

Scalable Strategies for Continual Learning with Replay Improving online continual learning performance and stability with temporal ensembles

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.905420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.877626Z digest=sha256:52f5b23123cb9da9947a2d0080994da06f334cfdff8cd61f6dc7b090732584b7

Observation 65709ad1-695d-4403-ace5-438c5a833753 · outbound

This paper cites Logit standardization in knowledge distillation.

Scalable Strategies for Continual Learning with Replay Logit standardization in knowledge distillation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.891410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.883576Z digest=sha256:921a0f999958e01e75e6693cfe0ca9b432d59bbd5db7909dd15195f7e4bc524e

Observation b9a7c7a7-16bb-434c-9c01-90c1c7832ad5 · outbound

This paper cites Three scenarios for continual learning.

Scalable Strategies for Continual Learning with Replay Three scenarios for continual learning

Reference 39

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unresolved
no resolver link, observed 2026-08-15T20:36:39.888750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.888750Z digest=sha256:249ebe860d4f6424b97badfec93d893e88109fc0f6fdb7721d2d7cd732f16f63

Observation 39782e8a-3ebb-47d3-908d-e82e2a40511a · outbound

This paper cites Continual Learning: Applications and the Road Forward.

Scalable Strategies for Continual Learning with Replay Continual Learning: Applications and the Road Forward

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.895084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.895084Z digest=sha256:b20574d709748f62842c865f9f5f2dbac3ceb5a0be913413e16d77486d38d247

Observation f1aaca85-2405-4aba-b369-c9fb4944ccae · outbound

This paper cites LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill Discovery.

Scalable Strategies for Continual Learning with Replay LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill Discovery

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.902351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.902351Z digest=sha256:de2b1c08f86d115641aaf77bd2b16bdf858c8c6863da894402b1957f0f8f08f9

Observation 1b7527e8-1669-4f8f-8b44-a4d7c65436ea · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Scalable Strategies for Continual Learning with Replay Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.908612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.908612Z digest=sha256:92a139805482b4eabd9475896b3f9ac401a2ce6490147204cd717ff89f8afcdb

Observation 245eb1cf-096e-44af-b060-9da2b18229c3 · outbound

This paper cites A Comprehensive Survey of Continual Learning: Theory, Method and Application.

Scalable Strategies for Continual Learning with Replay A Comprehensive Survey of Continual Learning: Theory, Method and Application

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.913971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.913971Z digest=sha256:6042781833438cac1da2a068a827fd052f3fafdbcde38895967aba9727b0e3fc

Observation c280793e-2621-45d2-949f-31769d41da21 · outbound

This paper cites HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning.

Scalable Strategies for Continual Learning with Replay HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.919886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.919886Z digest=sha256:9ec8b4284accfadc2ab10274a56b4e7540376a17de9c2fa91b994c677fe79d3f

Observation cad0bd5e-de43-4592-b323-ef15ef4e9faf · outbound

This paper cites Scaling Pre-training to One Hundred Billion Data for Vision Language Models.

Scalable Strategies for Continual Learning with Replay Scaling Pre-training to One Hundred Billion Data for Vision Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.924686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.924686Z digest=sha256:00fbd52c6a0b8fc39c2cf8f3f4766ecfa76829e51001be21480a7b250f402ef5

Observation 2a030f35-316d-49a6-b1a1-a327d3a076a4 · outbound

This paper cites Dualprompt: Com- plementary prompting for rehearsal-free continual learning.

Scalable Strategies for Continual Learning with Replay Dualprompt: Com- plementary prompting for rehearsal-free continual learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.876702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.929448Z digest=sha256:1515c47e4827f19916aef51ef2b32c329d857f957201b0cba1ae793a41a71d51

Observation 747174de-b0c3-410a-81e1-7a763d9dbf49 · outbound

This paper cites Learning to prompt for con- tinual learning.

Scalable Strategies for Continual Learning with Replay Learning to prompt for con- tinual learning

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.862286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.933407Z digest=sha256:6d27da56f30028561a05bdc0b276cafc12acc0c6968ca2416c3c0447c7163881

Observation 2701cef0-8d5b-4a49-aaa9-7a540a88dae8 · outbound

This paper cites Continual Learning with Low Rank Adaptation.

Scalable Strategies for Continual Learning with Replay Continual Learning with Low Rank Adaptation

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.938877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.938877Z digest=sha256:8075135258ec35c5d1e543c6a6ca3702b433a771de0234c821a018bcc82a454a

Observation 75944516-8a84-42d9-ab38-082a0b82108a · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-15T20:36:40.847535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.943806Z digest=sha256:addb118ec47f2ddd173a94c0007aab9b418e31b095c6cb93dd9926ac700c6d49

Observation a95ecb7e-e125-47fd-bedd-b7e95b2b3394 · outbound

This paper cites Ties-merging: Resolving interference when merging models.

Scalable Strategies for Continual Learning with Replay Ties-merging: Resolving interference when merging models

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.832841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.948484Z digest=sha256:57e5590261caad7ac7c25278c9892f21a2382ee24799966af0f60c81556ba9b7

Observation 09021c6b-cf5b-4ed8-9934-44ffd9b31f61 · outbound

This paper cites What Matters for Model Merging at Scale?.

Scalable Strategies for Continual Learning with Replay What Matters for Model Merging at Scale?

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.952965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.952965Z digest=sha256:8f8c402f3bf20cee1dbd42fb5166e551cf693f4eba0699dfbc70dd0114be6001

Observation 684d57f5-55f6-449c-9788-0f61bc491016 · outbound

This paper cites Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities.

Scalable Strategies for Continual Learning with Replay Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.958433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.958433Z digest=sha256:24909f8ef260cd29859687a3603be4b372e91f6afc262f9b5595765898d63973

Observation 5a7b8dc7-2c9d-47b7-af29-680c90fe9ff4 · outbound

This paper cites Continual Learners are Incremental Model Generalizers.

Scalable Strategies for Continual Learning with Replay Continual Learners are Incremental Model Generalizers

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:36:40.147891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.963383Z digest=sha256:d1e207b68b59c88ad6e13bea6e4e4d70b60aede76830208bdf03413bb8f5bdac

Observation b7fb3d7e-7836-4b2f-96f2-ca3acf4d7ecf · outbound

This paper cites Boosting continual learning of vision-language models via mixture-of-experts adapters.

Scalable Strategies for Continual Learning with Replay Boosting continual learning of vision-language models via mixture-of-experts adapters

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.815167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.968019Z digest=sha256:9606c0ab7c99092225ee7aa62ca37d497374e86211654bd888169a189b406dfa

Observation 682bb8c4-0519-4a91-aed8-9bffb16f6c31 · outbound

This paper cites Language models are super mario: Absorbing abilities from homologous models as a free lunch.

Scalable Strategies for Continual Learning with Replay Language models are super mario: Absorbing abilities from homologous models as a free lunch

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.798360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:39.977613Z digest=sha256:bb8828b8368d0c31fe4e4ed93566428f168f5c9d748cf3e506826be2a82a0581

Observation 49af8606-e438-4229-aee3-1729c705c914 · outbound

This paper cites When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method.

Scalable Strategies for Continual Learning with Replay When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.982811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.982811Z digest=sha256:3bb5f640d359dd65aa854ec7ac04b0898293b1333d3f53ae80eeb93f8e381005

Observation 738483fd-c6de-459c-bfb7-471a867d4dcf · outbound

This paper cites C-LoRA: Continual Low-Rank Adaptation for Pre-trained Models.

Scalable Strategies for Continual Learning with Replay C-LoRA: Continual Low-Rank Adaptation for Pre-trained Models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.988068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.988068Z digest=sha256:ab21197366887a5f290b06dc45ace94bcc116cbc873e971530a516b05f384d5a

Observation 561bb109-b054-4d2f-8d3e-f75c5540c614 · outbound

This paper cites Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models.

Scalable Strategies for Continual Learning with Replay Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.994817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.994817Z digest=sha256:b2d13933bdd5b891cdff98dbb4c69be2e391e45c2a92ed08fb03b4c6607f09f2

Observation 3d221bd1-4184-4cdc-8350-88d2d9ec76a2 · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-15T20:36:40.776185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:40.001203Z digest=sha256:fd44f1e28c19aab83adc8fbb6034229b7af96da7496490c8611480cece39e12d

Observation 8321aee1-8b30-488a-867c-8c0068008d87 · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-15T20:36:40.760425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:40.011692Z digest=sha256:e2ad9715b742e196a0abd9a9edaf11c7023f0858ab2e802aedf92c3136368517

Observation 96c8ffc4-0274-4c01-a541-9b3875b9665a · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-15T20:36:40.745781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:36:40.017952Z digest=sha256:ca17ce8f452558e058603500d97b269f2ed9283ee49adca11f01766c69962d5b

Pith citing papers

Observation 2f44ee6f-2ef0-49ec-a217-d0177ddb041c · inbound

Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training cites this paper.

Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training Scalable Strategies for Continual Learning with Replay

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:31:38.010166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T02:32:08.672114Z digest=sha256:75ea65e17a2cc7210e80d415d622beb938b0ef057fb621013f9d045335b272c9

Observation 1424c1d9-c3e7-409b-9289-51a06d2c05a3 · inbound

Diffract: Spectral View of LLM Domain Adaptation cites this paper.

Diffract: Spectral View of LLM Domain Adaptation Scalable Strategies for Continual Learning with Replay

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T15:52:45.940026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T15:52:45.940026Z digest=sha256:089dd94cb773bbc8bd95ae5f3838a509dc08e7fda0adf4a2a003a6e93af94e0f